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The Sign-Off Table

Lesson 5 of 5

Quality controls

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Integration and data architecture is only as good as its controls. Data enters through many doors, travels through interfaces and lands in analytics. Controls at each stage stop bad data early, detect what slips through and prove that what arrived equals what was sent. Architects specify these controls; testers and data owners prove they work.

Controls along the data path

  1. EntryValidation and derivation rules, mandatory fields, duplicate checks, approval for sensitive changes
  2. TransferSchema validation, mapping checks, guaranteed delivery, error queues with owners
  3. ArrivalReceiver confirmations, application-level checks, rejection with a reason
  4. ReconciliationCounts, amounts and key totals compared between sender and receiver
  5. MonitoringDashboards and alerts on failures, backlogs and data quality KPIs
Quality controls at each stage of the data path.
The Sign-Off Table · thesignofftable.com/academy/sap-arc-301

Preventive controls at entry

The cheapest defect is the one never created. In S/4HANA, master data governance can apply validation and derivation rules, duplicate checks and approval workflows before a record is activated. For transactional interfaces, the receiving application's own checks apply: an inbound sales order is validated like one entered by Maria's team. SAP Master Data Integration's documentation also lists schema validation among its features. Specify, per flow, which checks run and what happens to rejected data.

Governed master data passes validation, duplicate checks and approval before it becomes active.
The Sign-Off Table · thesignofftable.com/academy/sap-arc-301

Detective controls in transit

Every asynchronous interface needs monitoring with an owner. SAP Cloud ALM's Integration and Exception Monitoring links individual messages into end-to-end flows across cloud services and systems, lets users search for a message by business context such as an order number (if the component sends that context with the message) and raises alerts for error conditions. It maps each component's statuses into common status groups such as ERROR, WARNING, IN PROCESS and SUCCESSFUL. Design the business context attributes into each interface from the start; adding them later is much harder.

Business view"Where is portal order P-2025-0042 from Great Lakes Fleet Services?" searched by portal reference
Flow viewPortal → Cloud Integration → S/4HANA, one end-to-end flow with status per hop
AlertingError on the order flow → alert to the integration support queue with an assigned processor
Component viewEach system's own logs and queues, mapped to common status groups
Monitoring layers for interfaces, from business question to technical component.
The Sign-Off Table · thesignofftable.com/academy/sap-arc-301

Reconciliation

Reconciliation proves completeness and accuracy by comparing sender and receiver. It works at three levels: counts (records sent equals records received), totals (sums of amounts or quantities agree) and keys (the same set of identifiers on both sides). Reconciliation is required for migration loads and valuable for daily interfaces with financial impact.

Reconciliation checks counts, then totals, then keys; every difference is explained before Dan approves.
The Sign-Off Table · thesignofftable.com/academy/sap-arc-301
FlowCount checkTotal checkKey check
Wave 2 customer load1,946 customers in scope = 1,946 business partners createdNot applicableEvery in-scope legacy number appears as a reference
Wave 2 open AR loadOpen items per customerMXN 48,615,320.40 in legacy = open AR in company code 1910 at the key dateLegacy invoice numbers carried as references
MES production confirmationsConfirmations per shiftQuantity confirmed per orderOrder numbers
Bank statement filesStatements per accountOpening + movements = closing balanceStatement numbers in sequence

Contoso reconciliation controls by flow.

Data quality KPIs

  • Completeness: share of records with all mandatory attributes for their use.
  • Uniqueness: suspected duplicates per thousand business partners.
  • Timeliness: age of messages waiting in error queues; replication lag to the data platform.
  • Accuracy: share of sampled records that match their source documents.
  • Ownership: open data quality issues per data owner, with age.

What would you do?

Two weeks after go-live, finance finds that 37 MES production confirmations never reached S/4HANA. They had failed with a mapping error and sat in an error queue without alerts. What is the most important architectural fix?

Key points
  • Specify controls at entry, transfer, arrival, reconciliation and monitoring.
  • Prevent at entry with validation, duplicate checks and approvals.
  • Monitor every async flow with an owner, alerts and business context for search.
  • Reconcile counts, totals and keys; track data quality KPIs per owner.

Check your understanding · not graded

Lesson check

  1. 1. What three levels does reconciliation compare?

  2. 2. What does SAP Cloud ALM Integration and Exception Monitoring need to find a message by order number?

  3. 3. What is the target figure for reconciling the Wave 2 open AR load?

  4. 4. Which is a preventive control?